Modern businesses face data governance as a critical challenge. This topic is complex and can prove confusing even for experts. This article is designed to provide an answer to the question, What exactly is Data Governance?

Key takeaways

Companies must have data governance to ensure they are in control of their data. This is achieved by establishing data ownership standards, procedures, and regulations.

Data governance’s main goals include better regulatory compliance as well as higher quality data that is more suited for data analysis. Data governance training is available to help you master these skills in order to be able to manage your data more effectively.

Data governance provides benefits such as lower cost and higher efficiency, enhanced security, and transparent roles.

This article will provide examples and discuss the benefits of data governance tools. These will help to dispel common misconceptions and explain why every organization should have its data governance initiative.

Data governance: A simple definition

Data governance Institute defines data management as, paraphrased, “a system where decisions can be made and roles performed according to established rules.” These models make it easier to differentiate who can access the data and how.

One way to define data governance is that it refers to the section in data administration that establishes policies. Data governance programs comprise employees, processes, and technologies. They support data quality, better intelligence, and decision-making.

Actual examples of data Governance

These examples show how data management benefits every organization.

  1. Regulations

It is clear that both the government and the industry must enforce data governance programs. These regulations include the general data protection rules. This is because all EU businesses (which means most) must comply with the GDPR.

  1. Big data & analytics

Each day, businesses deal with data sets of over a petabyte in size. These data sets are often too large and complex for traditional software to handle. For this reason, predictive analytics are often used to extract value. The management of large amounts of data is much easier when there are three things you can do: Data governance, enterprise file synchronization, and sharing.

  1. Clearly defined responsibilities & role descriptions

Data governance eliminates all uncertainty about who manages data. It also makes it simpler for data-related plans to be made and decisions to be made. Data governance programs create clear roles that define the rules and guidelines for data management.

Why does data governance matter?

We’ll talk about the many reasons data governance has become so important. We will also be discussing the goals and benefits associated with data governance.

Data assets are different across systems and departments in a company. Adopting a good data governance program is essential. If the same file type reflects different naming practices in different business units within the enterprise, this could be an issue.

This could cause problems like slow data integration, issues with metadata, and errors in your data analytics software. These data errors can be missed and not corrected quickly. This could cause additional problems in the future.

All enterprises should agree on universal standards governing data formats and policies. This agreement ensures an understanding of corporate data. It also helps to avoid common errors and doubts that can arise from not adhering fully to the universal standards.